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Senior ML Infrastructure Engineer - Model Services



Software Engineering, Other Engineering, Data Science
Posted on Friday, May 24, 2024
OctoAI is a leading startup in the fast-paced generative AI market. Our mission is to empower businesses to build differentiated applications that delight customers with the latest generative AI features.
Our platform, OctoAI, delivers generative AI infrastructure to run, tune, and scale models that power AI applications. OctoAI makes models work for you by providing developers easy access to efficient AI infrastructure so they can run the models they choose, tune them for their specific use case, and scale from dev to production seamlessly. With the fastest foundation models on the market (including Llama-3, Stable Diffusion, and SDXL), integrated customization solutions, and world-class ML systems under the hood, developers can focus on building apps that wow their customers without becoming AI infrastructure experts.
Our team consists of experts in cloud services, infrastructure, machine learning systems, hardware, and compilers as well as an accomplished go-to-market team with diverse backgrounds. We have secured over $130M in venture capital funding and will continue to grow over the next year. We're based largely in Seattle but have a remote-first culture with people working all over the US and elsewhere in the world.
We dream big but execute with focus and believe in creativity, productivity, and a balanced life. We value diversity in all dimensions and are always looking for talented people to join our team!
Our ML engineering team is dedicated to developing the most efficient and feature packed engines for generative model deployment. The model services team builds the systems between the optimized GPU kernels and runtimes and the cloud platform where these models run. This includes feature enablement and optimization for popular media models, such as Mixtral, Llama-3, Stable Diffusion, SDXL, SVD, and SD3 and thus, requires broad understanding on a various system layers from the serving API to hardware-level.
We are seeking a highly skilled and experienced Machine Learning Infrastructure Engineer to join our dynamic team. In this role, you will be responsible for working with customers and the platform and ML Systems backend teams to build cutting-edge generative AI systems. In this senior role, this person will be responsible for contributing to the latest techniques and technologies in AI and machine learning. They will lead projects, mentor junior engineers, and play a crucial role in shaping the future of our ML systems.


  • Own, improve, and design next-generation AI serving systems.
  • Working closely with cloud platform and ML systems backend teams, customers, and product owners.
  • Keeping on top of new generative AI techniques and systems to enable feature development, system optimization, and improving internal and external DevEx.
  • Analyze production generative AI traffic to identify system bottlenecks and design, plan, and implement architectural improvements.
  • Develop impactful optimizations ranging from system-level to hardware-level.

What we look for:

  • Bachelor’s, Master’s, or PhD degree in Computer Science, Electrical Engineering, or a related field.
  • Extensive experience in machine learning systems engineering, with a proven track record of leading successful projects.
  • Strong programming skills in C/C++ and Python with a robust computer science background.
  • Experience in LLM inference systems is preferred but not required.
  • Familiarity with innovative open-source projects like MLC-LLM, vLLM, TGI is a plus.
  • Experience with machine learning compilers or frameworks such as TVM, MLIR, Pytorch, Tensorflow, ONNX Runtime, TensorRT is preferred.
  • Excellent problem-solving skills and the ability to work effectively in a fast-paced, dynamic environment.
  • Strong communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
We recognize that people come with experience and talent beyond just the technical requirements of a job. If your experience is close to what you see listed here, please still consider applying. Diversity of experience and skills combined with passion is a key to innovation and excellence. Therefore, we encourage people from all backgrounds to apply to our positions. Please let us know if you require accommodations during the interview process.
Diversity & Inclusion:
Our mission extends beyond technological breakthroughs; we aim to mirror the diverse world we serve. We understand the unique insights, creativity, and perspectives a diverse team can bring, and we're actively seeking to broaden our horizons. As we look to the future, we aim to address our current diversity gaps and set new industry standards for inclusivity.
Benefits Our Team Enjoys:
• Comprehensive Healthcare: Fully covered premiums for employees and their dependents, including Medical, Dental, Vision, Life Insurance, and Disability Insurance.
• Competitive Compensation: A mix of salary, bonuses, and meaningful stock options.
• Financial Benefits: Flexible Spending Accounts for healthcare and dependent care, as well as a Health Savings Account for those opting for a high deductible plan.
• Future Planning: 401(k) options.
• Flexible Work Options: Remote and teleworking capabilities.
• Work-Life Balance: Flexible work hours, generous time off policies, company-sanctioned downtime twice a year, and company-paid holidays.
• Parental Benefits: Comprehensive parental leave plans for all new parents.
• Volunteer Time Off (VTO): Four days a year to give back and make a difference in communities.
• Additional Leaves: Including disability, paid family medical leave, and paid military leave.
At OctoAI, we believe in creating an environment where everyone is valued and respected. Discrimination doesn't have a place in our culture. We evaluate individuals based on their abilities and effectiveness. We're committed to equal opportunity and ensuring that all qualified applicants receive consideration, free from biases related to race, color, religion, gender, identity, orientation, national origin, genetics, disability, age, or veteran status.